FORTE

FORTE (First Order Revision of Theories from Examples) is a machine
learning system for modifiying a first-order Horn-clause domain theory
to fit a set of training examples. FORTE uses a hill-climbing
approach to revise theories. It identifies possible errors in an
input theory and calls on a library of operators to develop possible
revisions. These operators are constructed from methods such as
propositional theory refinement, first-order induction, and inversion
resolution.

The FORTE system is available via anonymous ftp.
This system contains the following items: